Hybrid Physical - Deep Learning Models for Astronomical Inverse Problems
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Improved learning for materials and chemical structures through symmetry, hierarchy and similarity
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Deducing Inference from Hyperspectral Imaging of Materials Using Deep Recurrent Neural Networks
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Putting Non-Euclidean Geometry to Work in ML: Hyperbolic and Product Manifold Embeddings
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